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Jelena Milisavljevic SyedView profile

Senior Lecturer

• Manufacturing Systems
• Product and Service Design
• Design Thinking
• +7 more

Dr. Jelena Milisavljevic Syed is a Senior Lecturer in Manufacturing Systems at Cranfield University's Sustainable Manufacturing Systems Centre, with expertise spanning mechanical, control, and industrial engineering. Her academic journey includes positions at the University of Liverpool where she served as Lecturer in Industrial Design and Director of the Systems Realization Laboratory. Her educational background is impressive and diverse: PhD in Mechanical Engineering (Dynamic Management of Networked Engineered Manufacturing Systems) from University of Oklahoma MS in Mechanical Engineering (Uncertainty Management in Realization of Complex Manufacturing Systems) from University of Oklahoma MEng in Mechanical Engineering (Elastohydrodynamics Lubrication in Machines) from University of Nis, Serbia Diploma in Mechanical Technician for Computer-Aided Design from College of Mechanical Engineering Dr. Milisavljevic Syed's research focuses on integrating design thinking, strategy, and innovation management to realize cyber-physical product-service systems that adapt to dynamic market changes, supporting further digitalization in smart manufacturing. Her work bridges theoretical frameworks with practical industrial applications, particularly through her development of Design for Dynamic Management (DFDM) methodology. Analysis of her recent publications reveals a strong emphasis on sustainable manufacturing, digital transformation, and AI applications in supply chain management. Her work increasingly focuses on Industry 5.0 concepts, digital twins, and circular economy principles, reflecting the evolving landscape of modern manufacturing systems. The interdisciplinary nature of her research spans engineering, computer science, and sustainability domains. She maintains active professional memberships in several prestigious organizations: American Society of Mechanical Engineers (ASME) American Society for Engineering Education (ASEE) British Fluid Power Association (BFWG) Institution of Engineering and Technology (MIET) Institute of Electrical and Electronics Engineers (IEEE) Design Society Dr. Milisavljevic Syed currently supervises multiple PhD students working on cutting-edge research topics including AI-supported design for dynamic management, quality assurance frameworks for digital twins, and sustainable supply chain strategies. Her research addresses critical challenges in modern manufacturing, particularly focusing on how to adapt existing manufacturing systems to rapidly changing demand while maintaining sustainable production practices. She leads the Systems Realization Laboratory, which focuses on developing practical solutions for industry challenges through interdisciplinary collaboration between engineers, data scientists, and industry partners.

Feraz AzharView profile

Assistant Professor

• Philosophy of Science
• Philosophy of Physics
• Cosmology
• +4 more

Feraz Azhar is an Assistant Professor of Philosophy at the University of Notre Dame. His research bridges philosophy and physics , focusing on philosophy of science and philosophy of physics . Ph.D. in Philosophy , University of Cambridge Ph.D. in Theoretical Physics , University of California, Santa Barbara His work explores probability in primordial cosmology and philosophical aspects of black hole physics . Publications highlight his contributions to effective field theories , fine-tuning , and anthropic reasoning . Recent collaborations include cosmologists at Harvard University, focusing on cosmological models and epistemological frameworks .

Stephen AllumView profile

Senior Lecturer

• Process Safety
• Loss Prevention
• Quantified Risk Assessment
• +4 more

Stephen Allum is a Senior Lecturer at the University of Sheffield , affiliated with the School of Chemical, Materials and Biological Engineering . He serves as the Course Director for the MSc in Process Safety and Loss Prevention, contributing to postgraduate education and professional training. His research focuses on process safety , loss prevention , and quantified risk assessment , with expertise in applying these principles across industries like Oil & Gas, Nuclear Power, and Hazardous Waste. Stephen emphasizes simplifying complex safety challenges and fostering global collaboration through training programs. Chartered Engineer Chartered Environmentalist Contact: s.allum@sheffield.ac.uk , Room D23, Sir Robert Hadfield Building.

• Mathematics Education
• Sustainability Education
• Research Ethics
• +5 more

Professor Kjellrun Hiis Hauge is a faculty member at the University of Bergen within the Department of Language, Literature, Mathematics and Interpretation, specializing in mathematics education with interdisciplinary connections to ethics and sustainability. Her work bridges theoretical frameworks with practical educational applications across multiple contexts. Her research focuses on critical democratic competence development in mathematics, uncertainty in scientific inquiry, sustainability integration in early childhood and formal education, and combating misinformation through educational strategies. She examines how socio-political dimensions and ethical considerations can transform mathematics pedagogy to foster engaged citizenship and critical thinking skills. Recent publications (all 2024) demonstrate consistent thematic trends: integrating ethical reasoning into mathematics education, applying sustainability principles through interdisciplinary projects, and addressing global challenges via north-south collaborations. These works frequently employ case studies and collaborative frameworks to explore real-world applications of theoretical concepts. Professor Hauge actively supervises master's theses and teaches courses including Mathematics 1 (Foundational Mathematics), Mathematics 2 (Subject Perspectives and Problem-Solving), and Master's Thesis supervision. She contributes to the academic community as a member of the National Committee for Research Ethics in Science and Technology. She participates in two key research groups: Lived democracy , which explores democratic practices in educational settings, and Utdanning for bærekraft (Education for Sustainability), focusing on sustainable development integration across curricula.

• Facility Location
• Supply Chain Complexity
• Operations Research
• +5 more

Dr. Diego Ruiz-Hernandez serves as Senior Lecturer in Management Science at the University of Sheffield's Management School, where he directs the MSc Management program and belongs to the Operations Management and Decision Sciences department. His academic career spans Universitat Pompeu Fabra (1998-2009), Universidad de Navarra (2006-2009), University College for Financial Studies (2009-2018), with visiting positions at UK institutions including Edinburgh, Strathclyde, and Lancaster universities, plus Kedge Business School in Bordeaux. He holds a PhD in Operational Research from Universitat Pompeu Fabra in Catalonia, forming the foundation for his expertise in mathematical optimization and decision sciences. His professional journey reflects deep integration with both European academic institutions and industry collaborations. Ruiz-Hernandez's research centers on facility location theory, particularly banking network restructuring ('delocation' problems) and supply chain complexity measurement. He pioneered an entropy-based complexity metric satisfying rigorous internal/external consistency requirements, validated through partnerships with global firms. His work bridges theoretical operations research with practical applications in banking, healthcare, and renewable energy sectors, emphasizing mathematical modeling of proliferation effects and stochastic scheduling challenges. Recent publications reveal consistent focus on location-allocation problems with real-world constraints, evolving from banking restructuring to supply chain complexity and renewable energy maintenance. Key trends include entropy-based complexity metrics, bilevel programming for competitive environments, and restless bandit approaches for maintenance scheduling, all characterized by strong industry collaboration (notably BBVA) and methodological innovation in handling spatial, stochastic, and structural complexities. As an advisor, he supervised Xiaochen Feng's 2024 PhD on humanitarian evacuation modeling and actively recruits doctoral candidates for supply chain complexity and facility location research. He currently leads a BBVA-funded project on bank network restructuring while directing the Supply Chain, Operations and Logistics Applied Research Centre, where his team develops mathematical frameworks to mitigate complexity-driven profit erosion in global supply chains. His leadership extends to the Supply Chain, Operations and Logistics Applied Research Centre, where cross-disciplinary teams tackle complexity measurement, network restructuring, and stochastic resource allocation through industry-academia partnerships. Current initiatives focus on validating complexity control mechanisms and developing robust scheduling rules for large-scale maintenance operations under execution uncertainty.

• Sustainable Supply Chain Management
• Circular Supply Chain Management
• Blockchain Technology Applications
• +5 more

Dr Jason X. Wang serves as Lecturer in Sustainable Supply Chain Management within the Operations Management and Decision Sciences department at the University of Sheffield's Management School. Previously holding the position of MBA Programme Leader and Senior Lecturer at the University of Huddersfield, his academic focus centers on sustainable operations and supply chain innovation. His research program investigates sustainable and circular supply chain management through two primary lenses: customer-driven sustainability practices integrating carbon neutrality and circular product design, and blockchain technology applications enhancing supply chain transparency and resilience. This work extends to sustainability innovation in construction through prefabricated systems, addressing sector-specific challenges in environmental performance optimization. Analysis of his 15 most recent publications (2017-2025) reveals consistent emphasis on sustainability measurement, with significant application of event study methodology to quantify market reactions to environmental initiatives. Recent work increasingly employs advanced analytical techniques like fuzzy DEMATEL for barrier analysis, while maintaining strong focus on blockchain implementation challenges and decarbonization strategies across multiple industries. Dr Wang actively supervises PhD candidates in quantitative blockchain applications for sustainable supply chains and supply chain finance. His current research funding includes: £16,000 grant from The Productivity Institute investigating SME decision-making in technology-driven logistics productivity ESRC/The Productivity Institute project on strategic productivity for business leadership teams He contributes to the academic community as Editorial Review Board member for Journal of Supply Chain Management and IEEE Transactions on Engineering Management, while serving as Guest Editor for Transportation Research Part E and Senior Editor for Cogent Business & Management. Dr Wang is an active member of the Supply Chain, Operations and Logistics Applied Research Centre, where he develops industry collaborations including vehicle recovery services in New Zealand and UK motorsport sector sustainability initiatives.

Kristine Strada-RozenbergView profile

Professor

• Criminal Procedure Law
• Evidence Law
• Criminal Liability of Legal Entities
• +3 more

Kristine Strada-Rozenberg is a Professor at the Faculty of Law , University of Latvia , serving as Vice-Rector for Studies . Her research focuses on Criminal Procedure Law , Evidence Law , and Corporate Criminal Liability . Key achievements include leadership roles as Dean (2007–2015, 2021–2024) and Head of the Department of Criminal Law (2006–2007, 2016–2021). She has authored over 120 publications, including monographs and peer-reviewed articles on procedural fairness, victim rights, and EU law integration. 2024: Honorary Badge of the Justice System, First Class 2023: Golden Badge of the Ministry of the Interior Multiple Rector Gratitude Awards (2013, 2014, 2017, 2019, 2024) Her recent work analyzes criminal liability of legal entities , pre-trial detention , and harmonization of EU criminal law directives . She actively contributes to academic networks like the European Criminal Law Academic Network and serves on editorial boards of legal journals.

• Artificial Intelligence
• Robotics
• AI Safety
• +5 more

Siddharth Srivastava is an Associate Professor in the School of Computing and Augmented Intelligence at Arizona State University. His research focuses on developing principled, safe, and reliable AI systems that can learn generalizable knowledge for planning and accomplishing complex user-desired tasks under uncertainty. His educational background includes: PhD in Computer Science from the University of Massachusetts Amherst, working with Shlomo Zilberstein and Neil Immerman MS in Mathematics from the Indian Institute of Technology (IIT), Kanpur Dr. Srivastava's research interests span Artificial Intelligence, Robotics, AI Safety, and AI Assessment. He develops algorithms for generalizable planning and learning, with a focus on transfer learning, sequential decision making, and reinforcement learning. His work addresses the challenge of creating AI systems that can reliably (and safely) learn, generalize, and transfer knowledge to solve new tasks not encountered during training. His notable scientific awards include: NSF CAREER award Top 5% Faculty Award from the Fulton Schools of Engineering at ASU Best Paper Award at the International Conference on Automated Planning and Scheduling (ICAPS) Outstanding Dissertation award from UMass Amherst Best Final Year Thesis award from IIT Kanpur National Board of Higher Mathematics Scholarship Dr. Srivastava has advised several PhD students, including Pulkit Verma and Naman Shah (who recently defended their dissertations) and Rushang Karia. He leads the AAIR (Autonomous, Adaptive, and Intelligent Robotics) Lab at ASU, which focuses on developing principles and algorithms for reliable AI systems. The lab has organized workshops such as the GenPlan Workshop at NeurIPS and has been involved in significant events like the AAAI UR-RAD Symposium. His research has received press coverage from the BBC, Motherboard, AAAS Eureka Alert, NBC News, and IEEE Spectrum.

Ingrid HallandView profile

Associate Professor

• Material Culture
• Aesthetics
• Sustainable Design
• +7 more

Ingrid Halland is an Associate Professor at Oslo School of Architecture and Design and Aarhus University (Denmark), focusing on aesthetics and cultural philosophy. Her research bridges material culture , environmental ethics , artistic research , and Nordic design history , particularly examining titanium dioxide's ecological impact and modernist surface invisibility . She leads the Norges Forskningsråd-funded project How Norway Made the World Whiter (2023–2028) and co-leads The Materiality of White (DIKU, 2022–2025). Her scientific articles (2019–2024) explore material sustainability , surface aesthetics , and deep ecology through interdisciplinary lenses, including chemistry, biology, and cultural studies. Key themes include toxic material entanglements , speculative design , and historical material analysis . Halland founded and edits Metode , a platform for art and design research. She has received grants like the CAS Research Grant (2025–2026) and published books such as Ung Uro (2021) and the upcoming Deep White (2025). Her 2025 book White World Waste will further investigate pigment sustainability.

• Mergers and Acquisitions
• Behavioural Corporate Finance
• Corporate Governance
• +6 more

Yue Liu (also known as Lucy Liu) is a Senior Lecturer in Finance at the University of Edinburgh Business School. She holds a PhD in Finance from the University of Edinburgh, alongside an MSc in International Securities, Investment and Banking, an MBA, and a bachelor's degree in Engineering. Research Focus : Mergers and acquisitions, behavioural corporate finance, corporate governance, and content analysis of financial narratives, with interests in cognitive biases affecting corporate decisions. Teaching : Courses in Corporate Finance, Principles of Finance, and Behavioural Finance. Collaborations : Active in multi-author research on topics like ESG impacts, cybersecurity, and geopolitical risks. Awards : Nominated for the EUSA Teaching Award (2011-2012).

Hodjat PendarView profile

Lecturer

• Animal Locomotion
• Biomechanics
• Robotics
• +3 more

Hodjat Pendar is an Instructor in the Department of Mechanical Engineering at Virginia Tech, part of the College of Engineering. His research focuses on biomechanics, animal locomotion, robotics, and inverse problems, with particular emphasis on insect physiology and fluid dynamics. He holds a Ph.D. in Engineering Mechanics from Virginia Tech (2015), and M.Sc. and B.Sc. degrees in Mechanical Engineering from Sharif University of Technology (2004 and 2002, respectively). His research interests span biomechanical systems analysis, including the study of animal locomotion mechanics, fluid-structure interactions in robotics, and physiological responses to environmental factors like gravity. His work integrates computational tools for data inversion and uncertainty estimation, particularly in respirometry systems, and explores functional compartmentalization in insect circulatory systems. Pendar’s publications highlight trends in biomimetic robotics design, optimization of caudal fin dynamics for swimming efficiency, and the mechanical adaptations of insects to gravitational and hemolymph pressure challenges. His studies bridge mechanical engineering principles with biological systems, offering insights into both natural and engineered systems. No scientific awards are explicitly listed for Dr. Pendar. His advising and grant activities are not detailed in the provided information, and no affiliated labs or teams are mentioned.

• Numerical Weather Prediction
• Data Assimilation
• Severe Storms
• +5 more

Dr. Brian C. Ancell is a Professor in the Department of Geosciences at Texas Tech University, where he leads the Atmospheric Science Group. He specializes in numerical weather prediction, data assimilation, and the predictability of high-impact weather events. Dr. Ancell directs both a deterministic and ensemble real-time weather prediction system at Texas Tech University, providing forecast guidance at convection-allowing scales for operational and research purposes. B.S., Civil Engineering, University of Illinois, Urbana-Champaign, 1998 Ph.D. Atmospheric Science, University of Washington, Seattle, 2006 Dr. Ancell's research focuses on the predictability of high-impact weather events across various scales. His current work emphasizes severe convection, winter precipitation events, and wind power forecasting. He investigates how irrigation, wind farms, and urban heat islands contribute to non-local inadvertent weather modification. Using ensemble and adjoint sensitivity analysis, he develops tools to improve forecast accuracy for severe weather events and collaborates with the National Weather Service to transition these techniques into operational use. His work includes maintaining real-time deterministic and ensemble prediction systems at Texas Tech's High Performance Computing Center. Analysis of Dr. Ancell's recent publications reveals a strong focus on ensemble sensitivity techniques for improving high-impact weather prediction. His research demonstrates how ensemble-based methods can identify critical forecast sensitivities and improve probabilistic forecasting through ensemble subsetting. Much of his work bridges theoretical atmospheric science with practical applications in wind energy forecasting, severe storm prediction, and operational meteorology. His publications show increasing collaboration across disciplines, particularly in renewable energy applications and hydrological modeling. Dr. Ancell has secured significant research funding from multiple federal agencies including the National Science Foundation, National Oceanic and Atmospheric Administration, and Department of Energy, as well as industry partners like Shell Wind Energy. His $721,883 NSF CAREER award supports research on inadvertent weather modification and educational outreach through the Museum of Texas Tech University. He actively mentors graduate students, with multiple PhD and Master's students completing or working on research related to ensemble forecasting, severe weather prediction, and wind energy applications. Dr. Ancell serves as Associate Editor for three major meteorological journals and contributes to professional societies including the American Meteorological Society and American Geophysical Union. Dr. Ancell leads the Texas Tech real-time ensemble and deterministic weather prediction systems, which run on approximately 1,000 computing cores. These systems support operational forecasting applications, commercialization efforts, and research into advanced ensemble techniques. His work on the NSF-funded Big Weather Web project aims to establish computing infrastructure for university big data research in weather prediction. Through the Museum of Texas Tech University exhibit "How Weather Works: Our Place between the Sun and a Storm," he engages the public in understanding weather principles and human impacts on atmospheric processes.

Heng XiaoView profile

Professor

• Data-Driven Turbulence Modeling
• Uncertainty Quantification
• Computational Fluid Dynamics
• +5 more

Heng Xiao is a Professor of Data-Driven Fluid Dynamics at the University of Stuttgart, affiliated with the Institute of Aerospace Thermodynamics (ITLR) and the Cluster of Excellence EXC 2075 'Data-Integrated Simulation Science' in the Stuttgart Center for Simulation Science (SC SimTech). He previously served as Associate Professor (2020-2022) and Assistant Professor (2013-2020) at Virginia Tech, USA, and was a Postdoctoral Researcher/Lecturer at ETH Zürich (2009-2012). Ph.D., Civil Engineering, Princeton University, 2009 M.S., Scientific Computing, Royal Institute of Technology (KTH), 2005 B.S., Civil Engineering, Zhejiang University, 2003 His research focuses on integrating data science (machine learning, uncertainty quantification, data assimilation) with traditional physical models to advance predictive capabilities in multi-scale fluid systems. Key areas include Data-Driven Turbulence Modeling , Laminar-Turbulent Transition , Subsurface Flows , and Particle-Laden Flows . His work addresses turbulence modeling through neural operators, Bayesian inference, and physics-informed machine learning, with applications in aerospace, ocean engineering, and geosciences. Recent publications highlight trends in Neural Operators for Nonlocal Models , Ensemble Kalman Methods for Turbulence Inference , and Machine Learning for Permeability Prediction . Collaborative projects, such as the DFG-funded development of coupled turbulence and heat-flux models for film cooling, underscore his focus on real-world impact. Fellowship, Center of Turbulence Research Summer Program, Stanford University (2016) Finalist, Undergraduate Research Advisor Award, Virginia Tech (2014) Advisor to doctoral students including Jian-Xun Wang, Rui Sun, Jin-Long Wu, and Carlos Michelén-Ströfer, he leads the 'Data-Driven Fluid Dynamics' group at Stuttgart. The team collaborates with academia and industry, emphasizing high-performance computing and open-source tools like SediFoam for sediment transport simulations.

Dominic JohnsonView profile

Professor

• International Relations
• Evolutionary Biology
• Political Science
• +5 more

Dominic Johnson is the Alastair Buchan Chair of International Relations at the University of Oxford and a Fellow of St Antony's College. He holds dual PhDs in evolutionary biology (Oxford) and political science (Geneva). His work bridges evolutionary science and international relations, examining how cognitive biases, religion, and biological factors influence conflict, cooperation, and governance. Education: DPhil in Evolutionary Biology, University of Oxford PhD in Political Science, Geneva University MSc, MA (Geneva), and FISSR (Fellow of the International Society for Science and Religion) Research Interests: Johnson focuses on evolutionary dynamics in international relations, including cognitive biases' adaptive role in strategic decision-making, religion's evolutionary origins in fostering cooperation, and the intersection of science and governance. His work challenges traditional views by showing how 'irrational' traits like overconfidence or fear of supernatural punishment can enhance survival and political success. Awards & Recognition: 2006 International Studies Association Best Book Award for Failing to Win Fellow of the International Society for Science and Religion Key Roles: Co-Director, Oxford Martin School 'Natural Governance' Programme Co-Founder, Oxford Martin School Natural Governance Programme Distinguished Research Fellow, Changing Character of War Centre Labs/Initiatives: Leads research at the intersection of evolutionary science and policy through the Oxford Martin School Programme, exploring how evolutionary principles can improve global governance, conflict resolution, and ethical leadership.

Teruji ThomasView profile

Academic

• Ethics
• Decision Theory
• Formal Epistemology
• +5 more

Teruji Thomas is a Senior Research Fellow at the Global Priorities Institute within the Faculty of Philosophy at the University of Oxford. He holds a DPhil in Philosophy (2016) and a PhD in Mathematics (2006) from the University of Chicago. His research spans ethics, decision theory, formal epistemology, and the philosophy of science, with a focus on population axiology, moral decision-making under uncertainty, and anthropic reasoning. Thomas has held fellowships at the University of Edinburgh and Merton College, Oxford, and has transitioned from mathematics to philosophy, contributing interdisciplinary work. Education: 2016: DPhil, Philosophy, University of Oxford 2006: PhD, Mathematics, University of Chicago 2003: MPhil, Mathematics, University of Chicago Research Interests: Ethics (population ethics, aggregation, utilitarianism) Decision Theory (fanaticism, incompleteness) Formal Epistemology (anthropic reasoning, awareness) Philosophy of Mathematics and Physics Interdisciplinary projects on AI ethics and global priorities Teaching and Supervision: Supervised PhD students in ethics and decision theory Co-taught graduate courses on moral philosophy, political philosophy, and decision theory Labs/Teams: Active contributor to the Global Priorities Institute's research agenda on longtermism, existential risks, and effective altruism.